Abstract
A Multi objective, Multireservoir operation model for maximization of irrigation releases and maximization of hydropower production is proposed using Genetic Algorithm. These objectives are fuzzified and are simultaneously maximized by defining and then maximizing level of satisfaction (λ). In the present study a multireservoir system in Godavari River sub basin in Maharashtra State, India is considered. Problem is formulated with four reservoirs and a barrage. A monthly Multi Objective Genetic Algorithm Fuzzy Optimization (MOGAFUOPT) model for the present study is developed in ‘C’ Language. The optimal operation policy for maximization of irrigation releases, maximization of hydropower production and maximization of level of satisfaction is presented for existing demand in command area. The entire range of optimal operation policies, for different levels of satisfaction i.e. λ (ranging from 0 to 1), are determined. From the relationships developed amongst irrigation releases, hydropower production and level of satisfaction, a three dimensional (3-D) surface covering the whole range of policies has been developed. This solution surface can be the basis for decision makers for implementing the policies. Considering the future requirements in the command area, both the irrigation and hydropower demands are increased by 10 and 20%. The optimal operation policy for maximization of irrigation releases, maximization of hydropower production and maximization of level of satisfaction is also presented for these cases. The 3-D solution surface is also developed in these cases.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Al-Mohseen K, Khosa R (2002a) Long term operating policy for a single reservoir system via genetic algorithms—Part I. In: Proceedings of International Conference on Advances in Civil Engineering, ACE 2002, Kharagpur, pp 321–329
Al-Mohseen K, Khosa R (2002b) Long term operating policy for a single reservoir system via genetic algorithms – Part II. In: Proceedings of International Conference on Advances in Civil Engineering, ACE 2002, Kharagpur, pp 330–338
Anand Raj P (1995) Multicriteria methods in river basin planning – a case study. Water Sci Technol 31(8):261–272
Anand Raj P, Nagesh Kumar D (1996) Ranking of river basin alternatives using ELECTRE. J Hydrol Sci 41(5):697–713
Anand Raj P, Nagesh Kumar D (1997) Planning for sustainable development of a river basin using fuzzy logic. In: Proceedings of International Conference on Civil Engineering for Sustainable Development, Roorkee, India, pp 173–182
Bender MJ, Simonovic SP (2000) A fuzzy compromise approach to water resource systems planning under uncertainty. Fuzzy Sets Syst 115:35–44
Cai X, Mckinney D, Lasdon LS (2001) Solving nonlinear water management models using a combined genetic algorithm and linear programming approach. Adv Water Resour 2(6):667–676
Chang LC, Yang CC (2002) Optimizing the rule curves for multi-reservoir operations using a genetic algorithm and HEC-5. J Hydrosci Hydraul Eng 20(1):59–75
Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading, MA
Holland JH (1975) Adaptation in natural and artificial systems. University Michigan Press, Ann Arbor, MI
Labadie JW (2004) Optimal operation of multireservoir systems: state-of-the-art review. J Water Resour Plan Manage, ASCE 130(2):93–111
Loucks DP, Stedinger J, Haith D (1981) Water resources systems planning and analysis. Prentice-Hall, Eaglewood Cliffs, NJ
Nagesh Kumar D, Ashok, B., Srinivasa Raju K (2000) Application of genetic algorithms for optimal reservoir operation. In: Proceedings of X World Water Congress. Melbourne, Australia, CD-ROM
Nagesh Kumar D, Prasad DSV, Srinivasa Raju K (2001) Optimal reservoir operation using fuzzy approach. In: Proceedings of International Conference on Civil Engineering (ICCE-2001), Vol. II. Interline Publishing, Bangalore, India, pp 377–384
Ndiritu JG (2003) Reservoir system optimization using a penalty approach and a multi-population genetic algorithm. Water S A 29(3):273–280
Oliveira R, Loucks DP (1997) Operating rules for multi-reservoir systems. Water Resour Res 33(4):839–852
Reis LFR, Walters GA, Savic DE, Chaudhry FH (2005) Multi-reservoir operation planning using hybrid genetic algorithm and linear programming (GA-LP): an alternative stochastic approach. Water Resour Manag 19:831–848
Sharif M, Wardlaw R (2000) Multireservoir systems optimization using genetic algorithms: Case study. J Comput Civ Eng (ASCE) 14(4):255–263
Simonovic SP (2000) Tools for water management: one view of the future. Water Int (IWRA) 25(1):76–88
Srinivasa Raju K, Nagesh Kumar D (2004) Irrigation planning using genetic algorithms. Water Resour Manag 18:163–176
Tilmant A, Vanclooster M, Duckstein L, Persoons E (2002) Comparision of fuzzy and nonfuzzy optimal reservoir operating policies. J Water Resour Plan Manage (ASCE) 128(6):390–398
Wardlaw R, Sharif M (1999) Evaluation of genetic algorithm for optimal reservoir system operation. J Water Resour Plan Manage (ASCE) 125(1):25–33
Yeh WW-G (1985) Reservoir management and operations models: A state-of-the-art review. Water Resour Res 21(12):1797–1818
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Regulwar, D.G., Raj, P.A. Development of 3-D Optimal Surface for Operation Policies of a Multireservoir in Fuzzy Environment Using Genetic Algorithm for River Basin Development and Management. Water Resour Manage 22, 595–610 (2008). https://doi.org/10.1007/s11269-007-9180-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-007-9180-1